Merge pull request #340 from wsp-sag/revert-338-develop_with_ranch_ml…

…_node

Revert "assign ml node in the 950,000 range"

network_wrangler/roadwaynetwork.py

@@ -158,8 +158,6 @@ class RoadwayNetwork(object):
     SP_WEIGHT_FACTOR = 100
     MANAGED_LANES_NODE_ID_SCALAR = 500000
     MANAGED_LANES_LINK_ID_SCALAR = 1000000
-    MANAGED_LANES_NODE_ID_MIN= 950001
-    MANAGED_LANES_NODE_ID_MAX= 1000000
 
     SELECTION_REQUIRES = ["link"]
 
@@ -2174,20 +2172,12 @@ def _update_location_reference(location_reference: list):
             )
             return out_location_reference
 
-        # ml_links_df["A"] = (
-        #     ml_links_df["A"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
-        # )
-        # ml_links_df["B"] = (
-        #     ml_links_df["B"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
-        # )
-        unique_ids = pd.concat([ml_links_df['A'], ml_links_df['B']]).unique()
-        available_ids = (iter(range(RoadwayNetwork.MANAGED_LANES_NODE_ID_MIN, 
-                                    RoadwayNetwork.MANAGED_LANES_NODE_ID_MAX))
+        ml_links_df["A"] = (
+            ml_links_df["A"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
+        )
+        ml_links_df["B"] = (
+            ml_links_df["B"] + RoadwayNetwork.MANAGED_LANES_NODE_ID_SCALAR
         )
-        ml_node_mapping = {original_id: next(available_ids) for original_id in unique_ids}
-        ml_links_df["A"] = ml_links_df['A'].map(ml_node_mapping)
-        ml_links_df["B"] = ml_links_df['B'].map(ml_node_mapping)
-
         ml_links_df[RoadwayNetwork.UNIQUE_LINK_KEY] = (
             ml_links_df[RoadwayNetwork.UNIQUE_LINK_KEY]
             + RoadwayNetwork.MANAGED_LANES_LINK_ID_SCALAR